The Effects of Electronic Waste Burning on Lead Concentration in Water and Blood in South West Hebron: Descriptive-Comparative Study

Electronic waste (E-waste) is a collective name for all electronic devices which have been expired of their useful life periods like discarded computers, computer peripherals, mobile phones, televisions, and others. E-waste has increased the total waste volume and after dismantling and burning, it releases various toxic and carcinogenic gases and metals which are posing a threat to human health and also contaminate the environment (Kowsar, Khan et al. 2010).Great acknowledge to the European Union for their financial support, this project was totally funded by the European Union commission in Jerusalem, under the theme of PFP projects. Also the authors would like to acknowledge Mohammad Thaineh, Teacher Physiotherapy Department Ahliya University for their contributions and assistance during all over the study stages. Great thanks go to Eng. Safa Sultan for her contribution in editing and final conceptualization of the report. Many thanks also go to the two municipalities of South west Hebron and Halhul for their cooperation. Special thanks to all participants for their voluntary participation and their time. Finally thanks go to the Medical Relief Society for their kindly cooperation

α-Synuclein interacts directly but reversibly with psychosine: implications for α-synucleinopathies

Aggregation of α-synuclein, the hallmark of α-synucleinopathies such as Parkinson´s disease, occurs in various glycosphingolipidoses. Although α-synuclein aggregation correlates with deficiencies in the lysosomal degradation of glycosphingolipids (GSL), the mechanism(s) involved in this aggregation remains unclear. We previously described the aggregation of α-synuclein in Krabbe´s disease (KD), a neurodegenerative glycosphingolipidosis caused by lysosomal deficiency of galactosyl-ceramidase (GALC) and the accumulation of the GSL psychosine. Here, we used a multi-pronged approach including genetic, biophysical and biochemical techniques to determine the pathogenic contribution, reversibility, and molecular mechanism of aggregation of α-synuclein in KD. While genetic knock-out of α-synuclein reduces, but does not completely prevent, neurological signs in a mouse model of KD, genetic correction of GALC deficiency completely prevents α-synuclein aggregation. We show that psychosine forms hydrophilic clusters and binds the C-terminus of α-synuclein through its amino group and sugar moiety, suggesting that psychosine promotes an open/aggregation-prone conformation of α-synuclein. Dopamine and carbidopa reverse the structural changes of psychosine by mediating a closed/aggregation-resistant conformation of α-synuclein. Our results underscore the therapeutic potential of lysosomal correction and small molecules to reduce neuronal burden in α-synucleinopathies, and provide a mechanistic understanding of α-synuclein aggregation in glycosphingolipidoses.Fil: Abdelkarim, Hazem. University of Illinois; Estados UnidosFil: Marshall, Michael S.. University of Illinois; Estados UnidosFil: Scesa, Giuseppe. University of Illinois; Estados UnidosFil: Smith, Rachael A.. University of Illinois; Estados UnidosFil: Rue, Emily. University of Illinois; Estados UnidosFil: Marshall, Jeffrey. University of Illinois; Estados UnidosFil: Elackattu, Vince. University Of Illinois Chicago; Estados UnidosFil: Stoskute, Monika. University Of Illinois Chicago; Estados UnidosFil: Issa, Yazan. University Of Illinois Chicago; Estados UnidosFil: Santos, Marta. University Of Illinois Chicago; Estados UnidosFil: Nguyen, Duc. University Of Illinois Chicago; Estados UnidosFil: Hauck, Zane. University Of Illinois Chicago; Estados UnidosFil: Van Breemen, Richard B.. University Of Illinois Chicago; Estados UnidosFil: Celej, Maria Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigaciones en Química Biológica de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Centro de Investigaciones en Química Biológica de Córdoba; ArgentinaFil: Gaponenko, Vadim. University Of Illinois Chicago; Estados UnidosFil: Bongarzone, Ernesto R.. University Of Illinois Chicago; Estados Unido

Preliminary Design of a Receding Horizon Controller Supported by Adaptive Feedback

Receding horizon controllers are special approximations of optimal controllers in which the continuous time variable is discretized over a horizon of optimization. The cost function is defined as the sum of contributions calculated in the grid points and it is minimized under the constraint that expresses the dynamic model of the controlled system. The control force calculated only for one step of the horizon is exerted, and the next horizon is redesigned from the measured initial state to avoid the accumulation of the effects of modeling errors. In the suggested solution, the dynamic model is directly used without any gradient reduction by using a transition between the gradient descent and the Newton–Raphson methods to achieve possibly fast operation. The optimization is carried out for an "overestimated" dynamic model, and instead of using the optimized force components the optimized trajectory is adaptively tracked by an available approximate dynamic model of the controlled system. For speeding up the operation of the system, various cost functions have been considered in the past. The operation of the method is exemplified by simulations made for new cost functions and the dynamic control of a 4-degrees-of-freedom SCARA robot using the simple sequential Julia language code realizing Euler integration

Preliminary Design of a Receding Horizon Controller Supported by Adaptive Feedback

Receding horizon controllers are special approximations of optimal controllers in which the continuous time variable is discretized over a horizon of optimization. The cost function is defined as the sum of contributions calculated in the grid points and it is minimized under the constraint that expresses the dynamic model of the controlled system. The control force calculated only for one step of the horizon is exerted, and the next horizon is redesigned from the measured initial state to avoid the accumulation of the effects of modeling errors. In the suggested solution, the dynamic model is directly used without any gradient reduction by using a transition between the gradient descent and the Newton–Raphson methods to achieve possibly fast operation. The optimization is carried out for an "overestimated" dynamic model, and instead of using the optimized force components the optimized trajectory is adaptively tracked by an available approximate dynamic model of the controlled system. For speeding up the operation of the system, various cost functions have been considered in the past. The operation of the method is exemplified by simulations made for new cost functions and the dynamic control of a 4-degrees-of-freedom SCARA robot using the simple sequential Julia language code realizing Euler integration

Improvement of an Adaptive Robot Control by Particle Swarm Optimization-Based Model Identification

Model-based controllers suffer from the effects of modeling imprecisions. The analytical form of the available model often contains only approximate parameters and can be physically incomplete. The consequences of these effects can be compensated by adaptive techniques and by the improvement of the available model. Lyapunov function-based classic methods, which assume exact analytical model forms, guarantee asymptotic stability by cautious and slow parameter tuning. Fixed point iteration-based adaptive controllers can work without the exact model form but immediately yield precise trajectory tracking. They neither identify nor improve the parameters of the available model. However, any amendment of the model can improve the controller’s operation by affecting its range and speed of convergence. It is shown that even very primitive, fast, and simple versions of evolutionary computation-based methods can produce considerable improvement in their operation. Particle swarm optimization (PSO) is an attractive, efficient, and simple tool for model improvement. In this paper, a PSO-based model approximation technique was investigated for use in the control of a three degrees of freedom PUMA-type robot arm via numerical simulations. A fixed point iteration (FPI)-based adaptive controller was used for tracking a nominal trajectory while the PSO attempted to refine the model. It was found that the refined model still had few errors, the effects of which could not be completely neglected in the model-based control. The best practical solution seems to be the application of the same adaptive control with the use of the more precise, PSO-improved model. Apart from a preliminary study, the first attempt to combine PSO with FPI is presented here

Design and implementation of auto car driving system with collision avoidance

This paper presents designing and manufacturing the hardware and software of a low-cost robotic system, which can be installed into any petrol car with an automatic gearbox, giving the ability to a car to be driverless. The proposed approach is composed of three systems; first, a computer vision system detects the lane located ahead of the vehicle to provide a reference angle for the steering wheel; second, to make the proper decision, a control and collision avoidance system are implemented, which are responsible for collecting sensors data and perform the right action by applying a closed-loop control system; third, the electro-mechanical system, which physically controls the steering wheel, braking and accelerating of the vehicle by actuators. The proposed system has been tested on-ground in several experiments and returned with acceptable results

A Specific Encoding Scheme for Genetic Stereo Correspondence Searching: Application to Obstacle Detection

Stereo correspondence is one of the most active research areas in computer vision. It consists in identifying features in two or more stereo images that are generated by the same physical feature in the three-dimensional space. In our approach, the matching problem is first turned into an optimization task where a fitness function, representing the constraints on the solution, is to be minimized. The optimization process is then performed by means of a genetic algorithm with a new encoding scheme. Experimental results are presented to demonstrate the robustness and the reliability of the proposed approach for obstacle detection in front of a vehicle using linear stereo vision

Mise en correspondance stéréoscopique par algorithmes génétiques (nouveaux codages)

Un des objectifs de la vision artificielle est de percevoir le relief d'un environnement à partir d'une ou plusieurs images. La vision binoculaire constitue l'une des méthodes les plus utilisées dans ce domaine. Il s'agit de retrouver la géométrie spatiale d'une scène à partir de deux images prises sous des angles différents. Une des principales difficultés de cette méthode est la mise en correspondance d'indices visuels extraits des images stéréoscopiques. Les techniques séquentielles ou multi-résolutions ayant montré leurs limites, nous présentons dans cette thèse une approche globale pour la mise en correspondance de primitives de type point de contour. Dans cette approche l'appariement stéréoscopique est considéré comme un problème d'optimisation dont la résolution est basée sur les concepts de calcul génétique. Grâce à un codage spécifique, une fonction d'évaluation des solutions (fonction fitness) est construite à partir des contraintes stéréoscopiques. Un algorithme génétique est ensuite mis en oeuvre pour explorer l'espaces des solutions, à partir d'une population initiale de solutions et par application des opérations de sélection, de croisement et de mutation. Afin de réduire la complexité du problème de mise en correspondance, nous proposons une stratégie hiérarchique de recherche des appariements. L'évaluation de nos algorithmes de mise en correspondance, appliqués sur de nombreuses images stéréoscopiques, montre l'intérêt de notre approche pour la reconstruction 3D d'une scène. L'implémentation des procédures développées sur des structures parallèles spécifiques pennettraient d'améliorer les temps d'exécutions et d'envisager une exploitation effective du procédé.Un des objectifs de la vision artificielle est de percevoir le relief d'un environnement à partir d'une ou plusieurs images. La vision binoculaire constitue l'une des méthodes les plus utilisées dans ce domaine. Il s'agit de retrouver la géométrie spatiale d'une scène à partir de deux images prises sous des angles différents. Une des principales difficultés de cette méthode est la mise en correspondance d'indices visuels extraits des images stéréoscopiques. Les techniques séquentielles ou multi-résolutions ayant montré leurs limites, nous présentons dans cette thèse une approche globale pour la mise en correspondance de primitives de type point de contour. Dans cette approche l'appariement stéréoscopique est considéré comme un problème d'optimisation dont la résolution est basée sur les concepts de calcul génétique. Grâce à un codage spécifique, une fonction d'évaluation des solutions (fonction fitness) est construite à partir des contraintes stéréoscopiques. Un algorithme génétique est ensuite mis en oeuvre pour explorer l'espaces des solutions, à partir d'une population initiale de solutions et par application des opérations de sélection, de croisement et de mutation. Afin de réduire la complexité du problème de mise en correspondance, nous proposons une stratégie hiérarchique de recherche des appariements. L'évaluation de nos algorithmes de mise en correspondance, appliqués sur de nombreuses images stéréoscopiques, montre l'intérêt de notre approche pour la reconstruction 3D d'une scène. L'implémentation des procédures développées sur des structures parallèles spécifiques pennettraient d'améliorer les temps d'exécutions et d'envisager une exploitation effective du procédé.LILLE1-BU (590092102) / SudocSudocFranceF

EFL Teachers' Challenges and Coping Strategies in Emergency Remote Teaching During the COVID-19 Pandemic

Kuwait is one of the countries whose educational systems have suffered deeply following the governmental precautionary procedures which enforced the closure of schools to restrict the breakout of the virus. Affected dramatically by the consequences of the pandemic, this chapter focused on the challenges, strategies, and responses of English as a foreign language (EFL) teachers about the problems that emerged during the COVID-19 pandemic. Findings revealed that the greatest challenges they faced during online teaching were assessing students and keeping them involved during classes, teaching the writing skill, time constraints, and technical problems. Moreover, teachers showed low levels of difficulty in managing their online classrooms because of the support and cooperation of school administrations regarding students' behavior in online lessons